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Assessing Airbnb Logistics in Cities: Geographic Information System and Convenience Theory

Author

Listed:
  • Zhihua Zhang

    (Department of Civil and Environmental Engineering, the University of Tennessee, Knoxville, TN 37996-2313, USA)

  • Rachel J.C. Chen

    (Department of Retail, Hospitality, and Tourism Management, the University of Tennessee, 246 Jessie Harris Building, Knoxville, TN 37996-1911, USA)

Abstract

City managers and planners seek insights into Airbnb logistics in cities for the purposes of effective lodging management. This requires managers and planners to gain a holistic understanding of Airbnb geographic dynamics, which has drawn limited attention in the literature. To fill this gap, this paper explored Airbnb supply and logistics in three cities (New York City, Los Angeles, and Chicago) through the lenses of geographic clustering and location convenience. We explored the spatial allocations of Airbnb supply in cities and investigated Airbnb’s influencing factors at the census tract level, utilizing spatial regression models. The results showed that (1) the spatial distribution of Airbnb supply in all three cities has a clear center-peripheral pattern, indicating that Airbnb allocations predominate in the central area of the city; (2) the number of housing units and points of interest (POI) have an influential impact on Airbnb supply for three cities; (3) the proportion of youth population and employment has a positive effect on Airbnb supply in NYC and Chicago, but not in LA, while the distance to the city center negatively affects Airbnb supply in LA and Chicago, but not in NYC; (4) the income has a mixed effect on Airbnb supply in three cities, while the proportion of African Americans and education level has only a positive effect on Airbnb supply in NYC; and (5) rent is not associated with Airbnb supply for all three cities, which indicates that the Airbnb explosion may not contribute to rent increases in cities.

Suggested Citation

  • Zhihua Zhang & Rachel J.C. Chen, 2019. "Assessing Airbnb Logistics in Cities: Geographic Information System and Convenience Theory," Sustainability, MDPI, vol. 11(9), pages 1-11, April.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:9:p:2462-:d:226096
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    References listed on IDEAS

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    Cited by:

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    2. Yifei Jiang & Honglei Zhang & Xianting Cao & Ge Wei & Yang Yang, 2023. "How to better incorporate geographic variation in Airbnb price modeling?," Tourism Economics, , vol. 29(5), pages 1181-1203, August.
    3. Donghwan Ki & Sugie Lee, 2019. "Spatial Distribution and Location Characteristics of Airbnb in Seoul, Korea," Sustainability, MDPI, vol. 11(15), pages 1-16, July.
    4. Ao Sun & Lin Chen & Kunimitsu Yoshida & Meng Qu, 2023. "Spatial Patterns and Determinants of Bed and Breakfasts in the All-for-One Tourism Demonstration Area of China: A Perspective on Urban–Rural Differences," Land, MDPI, vol. 12(9), pages 1-21, September.
    5. Shijie Sun & Shengyue Zhang & Xingjian Wang, 2021. "Characteristics and influencing factors of Airbnb spatial distribution in China’s rapid urbanization process: A case study of Nanjing," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-19, March.
    6. Zhihua Zhang & Rachel J. C. Fu, 2020. "Accommodation Experience in the Sharing Economy: A Comparative Study of Airbnb Online Reviews," Sustainability, MDPI, vol. 12(24), pages 1-11, December.
    7. Laura Serrano & Antonio Sianes & Antonio Ariza-Montes, 2020. "Understanding the Implementation of Airbnb in Urban Contexts: Towards a Categorization of European Cities," Land, MDPI, vol. 9(12), pages 1-21, December.

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